Standardization for improved Spatio-Temporal Image Fusion
This work addresses a domain-specific problem for remote sensing and image fusion researchers, offering incremental improvements in standardization techniques.
The paper tackled the problem of standardizing images for Spatio-Temporal Image Fusion (STIF) by proposing two methods: traditional upscaling and a sharpening approach called ABSIS, which increased spectral and spatial accuracies by up to 49.46% and 78.40%, respectively, for the USTFIP method.
Spatio-Temporal Image Fusion (STIF) methods usually require sets of images with matching spatial and spectral resolutions captured by different sensors. To facilitate the application of STIF methods, we propose and compare two different standardization approaches. The first method is based on traditional upscaling of the fine-resolution images. The second method is a sharpening approach called Anomaly Based Satellite Image Standardization (ABSIS) that blends the overall features found in the fine-resolution image series with the distinctive attributes of a specific coarse-resolution image to produce images that more closely resemble the outcome of aggregating the fine-resolution images. Both methods produce a significant increase in accuracy of the Unpaired Spatio Temporal Fusion of Image Patches (USTFIP) STIF method, with the sharpening approach increasing the spectral and spatial accuracies of the fused images by up to 49.46\% and 78.40\%, respectively.